Solid state imager devices, including charge coupled devices (CCD) and CMOS imagers, among other types, have been used in photo imaging applications. A solid state imager device includes a focal plane array of pixel cells, each one of the cells including a photosensor, which may be a photogate, photoconductor or a photodiode having a doped region for accumulating photo-generated charge.
During the manufacture of solid state imager devices, the creation of defective pixels is unavoidable. Some of the pixels in the imager device may be always dark (often due to shorts) or always too bright (often due to abnormally high leakage current). These defective pixels, if not corrected, can cause severe degradation of image quality and, as a result, decrease the yield of parts during production. Thus, minimization of these pixel defects during fabrication using close manufacturing tolerances will yield a higher quality product. However, it is usually less expensive to make an imager device using less precise manufacturing tolerances. In general, semiconductor devices produced using less precise manufacturing tolerances have a higher probability of defects. Typical semiconductor fabrication rules define some tradeoff between the quality (i.e., lack of defects) and cost of manufacture. The manufactured semiconductor devices are tested for defects, and any semiconductor device having more than a certain number of defects is usually discarded.
Image acquisition semiconductor devices (i.e., imager devices) are sensitive to pixel defects and a sensor with such defects may not yield aesthetically pleasing images. It is especially evident when defects are located in low frequency areas or at image contour edges. Edges in images are areas with strong intensity contrasts. A bad pixel in an imager device will show up as a bad area on the acquired image. The defective pixels may not work at all or, alternatively, they may be significantly brighter or dimmer than expected for a given light intensity. Depending on the desired quality and the intended application, a single defective pixel may sometimes be sufficient to cause the imager device containing the pixel to be discarded.
In most instances, however, a small percentage of defective pixels can be tolerated and compensated for. Numerous techniques exist for locating and correcting single defective pixels in an imager device. Correction of multiple defective pixels in a small area of an array, termed “cluster defects” or “defective pixel clusters,” however, presents increased challenges. Accurate location of these pixel cluster defects is one of those challenges.
One simple technique for correcting defective pixels involves taking a signal from each pixel in an array and storing the pixel signal values in memory. During image processing, the saved value for a defective pixel can be replaced by a signal value which is based on one or more signals from the neighboring pixels of the defective pixel. For example, the defective pixel signal can be substituted for an adjacent pixel signal value or for an average of the signal values from more than one pixel in the neighboring area of the pixel array.
These substitution techniques rely on accurate knowledge of the defective pixel locations. One of the widely used methods for determining the locations of defective pixels is off-line testing performed at the time of imager device fabrication at a factory. The defective pixel location determined during this off-line testing can be stored in a non-volatile memory in the imager device. The main disadvantage to this approach is that the number of defects that can be corrected is limited by the size of non-volatile memory dedicated to this purpose. Another drawback of this approach is that it requires a separate manufacturing step for the identification and storage of the pixel defect locations on the imager chip itself.
On the other hand, “on-the fly” cluster correction methods, i.e., those performed during use of the imager device rather than at the time of manufacture, have difficulties distinguishing between “true” defects and small image elements in the presence of arbitrary image content, and therefore, can lead to a more destructive image. This is particularly true for detection of “true” cluster defects.
Accordingly, there is a need and desire for a method, apparatus and system capable of accurately locating pixel defects, for example, pixel cluster defects, in a pixel array during use of an imager device.